x.y.z contains additional preinstalled Python packages (see below). This is the recommended tag for most Rivanna users.x.y.z-<user> is a custom container prepared for a specific user.All are GPU-compatible.
module load singularity
singularity pull docker://uvarc/pytorch:x.y.z
singularity run --nv pytorch_x.y.z.sif your_script.py
| Package\PyTorch | 1.12.0 | 1.10.0 | 1.8.0/1 | 1.7.0 | 1.6.0 |
|---|---|---|---|---|---|
| Python | 3.9.13 | 3.8.12 | 3.7.3/3.8.8 | 3.7.3 | 3.7.3 |
| NumPy | 1.23.1 | 1.20.1 | 1.20.1 | 1.19.2 | 1.19.1 |
| SciPy | 1.8.1 | 1.6.1 | 1.6.1 | 1.5.3 | 1.5.2 |
| TorchVision | 0.13.0 | 0.11.1 | 0.9.0/1 | 0.8.1 | 0.7.0 |
| Torchaudio | 0.12.0 | 0.10.0 | 0.8.0/1 | 0.7.0 | 0.6.0 |
| PyTorch Lightning | 1.6.5+ | 1.5.3+ | 1.2.1+ | 1.0.3 | 0.8.5 |
| TorchText | 0.13.0 | 0.11.0 | 0.9.0/1 | 0.8.0 | 0.7.0 |
| BoTorch | 0.6.5 | 0.5.1 | 0.4.0 | 0.3.2 | 0.3.0 |
| Ignite | 1.1.0 | 1.1.0 | 1.1.0 | 1.1.0 | 0.4.1 |
| LightGBM | 2.3.1 | ||||
| Matplotlib | 3.5.2 | 3.5.0 | 3.3.4 | 3.3.2 | 3.3.0 |
| Seaborn | 0.11.2 | 0.11.2 | 0.11.1 | 0.11.0 | 0.10.1 |
| Pandas | 1.4.3 | 1.3.4 | 1.2.3 | 1.1.3 | 1.1.0 |
| Scikit-learn | 1.1.1 | 1.0.1 | 0.24.1 | 0.23.2 | 0.23.2 |
| Scikit-image | 0.19.3 | 0.18.3 | 0.18.1 | 0.17.2 | 0.17.2 |
| OpenSlide-Python | 1.2.0 | 1.1.2 | 1.1.2 | 1.1.2 | 1.1.1 |
| OpenCV | 4.6.0.66 | 4.5.4.60 | 4.5.1.48 | 4.4.0.44 | 4.3.0.36 |
To install more packages:
/path/to/sif -m pip install --user <package>
Content type
Image
Digest
sha256:7ff1ea3f6…
Size
9.1 GB
Last updated
about 3 years ago
docker pull uvarc/pytorch:2.0.1